Differential gene expression by integrin β7+ and β7- memory T helper cells
© Rodriguez et al; licensee BioMed Central Ltd. 2004
Received: 12 February 2004
Accepted: 05 July 2004
Published: 05 July 2004
The cell adhesion molecule integrin α4β7 helps direct the migration of blood lymphocytes to the intestine and associated lymphoid tissues. We hypothesized that β7+ and β7- blood memory T helper cells differ in their expression of genes that play a role in the adhesion or migration of T cells.
RNA was prepared from β7+ and β7- CD4+ CD45RA- blood T cells from nine normal human subjects and analyzed using oligonucleotide microarrays. Of 21357 genes represented on the arrays, 16 were more highly expressed in β7+ cells and 18 were more highly expressed in β7- cells (≥1.5 fold difference and adjusted P < 0.05). Several of the differentially expressed transcripts encode proteins with established or putative roles in lymphocyte adhesion and chemotaxis, including the chemokine receptors CCR9 and CCR10, the integrin α4 subunit, L-selectin, KLRB1 (CD161), NT5E (CD73), LGALS1 and LGALS2 (galectin-1 and -2), and RGS1. Flow cytometry was used to determine whether differences in levels of transcripts encoding cell surface proteins were associated with differential expression of those proteins. Using this approach, we found that surface expression of KLRB1, LAIR1, and NT5E proteins was higher on β7+ memory/effector T cells than on β7- cells.
Memory/effector T cells that express integrin β7 have a distinct pattern of expression of a set of gene transcripts. Several of these molecules can affect cell adhesion or chemotaxis and are therefore likely to modulate the complex multistep process that regulates trafficking of CD4+ memory T cell subsets with different homing behaviors.
Lymphocyte migration is a multistep process that involves a complex interplay between adhesion molecules and chemokines and their G protein-coupled receptors [1, 2]. Naïve T cells express the adhesion molecule L-selectin, the chemokine receptor CCR7 and other molecules that allow these cells to migrate preferentially to secondary lymphoid organs where they can encounter antigen-presenting cells. When presented with appropriate antigens, these T cells can differentiate into memory T cells. Some memory cells continue to express L-selectin and/or CCR7 and to migrate efficiently to secondary lymphoid organs, whereas others lose expression of these molecules and instead express other molecules that direct migration (or "homing") to other organs [1, 2].
Extensive investigation has helped to define the role of some adhesion molecules and chemokine receptors in CD4+ memory T cell homing to the skin and the gut. The adhesion molecule cutaneous lymphocyte antigen (CLA) and the cutaneous T cell-attracting chemokine receptor CCR10 help control T cell homing to the skin [3–8]. The adhesion molecule integrin α4β7 and the chemokine receptor CCR9 play key roles in homing of lymphocytes to the intestine and Peyer's patches [9–13]. Integrin α4β7 is a receptor for mucosal addressin cell adhesion molecule-1 (MAdCAM-1), a glycoprotein that is expressed by gut endothelium. CCR9 is a receptor for the chemokine TECK (CCL25), which is expressed by endothelial cells and other cells in the small intestine [14, 15]. The adhesion molecule and chemokine receptor expression pattern of memory/effector CD4+ T cells is strongly influenced by whether initial T cell activation takes place in cutaneous or intestinal lymph nodes [16–18]. Recent evidence suggests that T cell homing receptor expression patterns are "imprinted" by dendritic cells during antigen presentation [19–21]. Although many other molecules have been shown to help control lymphocyte adhesion or migration, it is not clear which if any of these are selective expressed in gut homing memory CD4+ T cells.
We used DNA microarrays to systematically compare RNA transcript expression in human blood β7+ and β7- CD4+ memory T cells. We identified a substantial number of differentially expressed genes, many of which have been previously shown to have effects on cell adhesion and migration. In addition, we showed that some of these transcript expression differences were reflected in differences in surface expression of the encoded proteins.
Microarray analysis of differential gene expression by β7+ and β7- CD4+ memory T cells
Gene transcripts with higher expression in β7+ versus β7- CD4+ CD45RA- T helper cells*
chemokine (C-C motif) receptor 9
chemokine (C-C motif) ligand 5
transcription factor RAM2
leucine rich repeat neuronal 3
growth factor independent 1
integrin, alpha 4 (CD49D)
CD1C antigen, c polypeptide
killer cell lectin-like receptor subfamily B, member 1
leukocyte-associated Ig-like receptor 1
ribonucleotide reductase M2 polypeptide
Homo sapiens cDNA FLJ32290 fis, clone PROST2000463
expressed in hematopoietic cells, heart, liver
interleukin 18 receptor accessory protein
sterol regulatory element binding transcription factor 1
killer cell lectin-like receptor subfamily G, member 1
lectin, galactoside-binding, soluble, 2 (galectin 2)
Gene transcripts with higher expression in β7- versus β7+ CD4+ CD45RA- T helper cells*
G protein-coupled receptor 2 (CCR10)
regulator of G-protein signalling 1
tripartite motif-containing 2
chromosome 1 open reading frame 24
calmodulin binding transcription activator 1
lectin, galactoside-binding, soluble, 1 (galectin 1)
purinergic receptor P2Y, G-protein coupled, 5
selectin L (lymphocyte adhesion molecule 1)
similar to RIKEN cDNA 1700007B22
chondroitin beta1,4 N-acetylgalactosaminyltransferase
similar to BcDNA:GH11415 gene product
protein tyrosine phosphatase-like, member a
mannose receptor, C type 2
prion protein (p27-30)
pleckstrin homology-like domain, family A, member 1
Comparison of surface protein expression on β7+ and β7- CD4+ memory T cells
Surface expression of five gene products on β7+ versus β7- CD4+ T cells
Mean surface protein expression*
Fold difference: Transcript**
Fold difference: Surface protein***
CD45RA- β7+ cells
CD45RA- β7- cells
+2.5 (+1.6 to +3.9)
+2.5 (+2.2 to +3.6)
1.0 (-3.2 to +2.1)
+1.7 (+1.2 to +3.2)
-1.8 (-2.1 to -1.5)
We used DNA microarrays to identify gene transcripts that were differentially expressed on the subset of CD4+ memory/effector T cells that express integrin β7. Since the overwhelming majority of β7+ cells in blood express the gut homing receptor integrin α4β7, this approach was designed to identify genes that might play a role in organ-specific homing. We identified 16 transcripts that were more highly expressed in β7+ cells and 18 that were more highly expressed on β7- cells. We can relate transcript expression to expression of protein in seven cases (Table 3 and refs. [8, 13]). In six of these cases (CCR9, GPR2/CCR10, KLRB1, LAIR1, NT5E, and SELL), differential transcript expression was accompanied by differential expression of the corresponding protein on the surface of β7+ versus β7- cells. In one case (KLRG1), we did not find evidence for a consistent difference in surface protein expression (Table 3). These data suggest that most of the differentially expressed transcripts correspond to differentially expressed proteins, although it will be important to confirm this directly when suitable reagents become available.
Some of the differentially expressed transcripts encode proteins with known roles in organ-specific homing. The two most highly differentially expressed genes we detected in our analysis encode chemokine receptors already shown to have important roles in gut and non-gut (skin) homing. These are CCR9, the TECK/CCL25 receptor which is expressed preferentially on α4β7+ gut homing cells , and GPR2/CCR10, the CTACK/CCL27 receptor which is expressed preferentially on CLA+ skin homing cells . We found that transcripts encoding the α subunit (ITGA4) of integrin α4β7, was more highly expressed in β7+ cells. The microarray experiments indicated that the transcript encoding the β7 subunit itself (ITGB7) was not differentially expressed, consistent with previous results obtained using quantitative RT-PCR (M.W.R and D.J.E, unpublished results). This suggests that surface expression of the α4β7 heterodimer on CD4+ memory T cells may be determined primarily by the amount of α4 subunit available and not by the amount of β7 produced. The other differentially expressed transcript with a known role in homing is SELL, which encodes the peripheral lymph node homing receptor L-selectin (CD62L). We found that expression of both L-selectin transcript and surface protein was higher in β7- than β7+ memory/effector T cells. Although many β7-expressing memory cells also expressed L-selectin, cells expressing the highest levels of β7 did not express L-selectin (Fig. 2). This presumably contributes to the development of CD4+ T cell subsets with distinct homing properties.
We also found evidence that β7+ and β7- cells differ in their expression of other molecules that have been reported to modulate cell adhesion and migration. KLRB1 transcript and surface protein expression was higher on β7+ memory effector T cells. Overexpression of KLRB1 (also known as CD161 or NKRP1A) was previously found to increase transendothelial migration of CD4+ T cells, perhaps by modulating integrin activity . The finding that KLRB1 was preferentially expressed on T cells from human intestine led to a recent suggestion that KLRB1 may help direct intestinal homing . This hypothesis remains to be tested, but would be consistent with our finding of preferential expression of KLRB1 on β7+ blood memory CD4+ T cells. We also found higher expression of NT5E (CD73) transcripts and surface protein on β7+ memory effector T cells. NT5E is an ecto 5'-nucleotidase expressed on lymphocytes and on endothelial cells and has been reported to mediate lymphocyte-endothelial adhesion and transmigration by various mechanisms, including promotion of integrin-mediated binding via effects on integrin clustering [33–36]. Transcripts encoding two members of the galectin family were differentially expressed on β7+ versus β7- cells. Both LGALS1/galectin-1 (expressed at higher levels in β7- cells) and LGALS2/galectin-2 (expressed at higher levels in β7+ cells) have been shown to have several effects on cell adhesion in lymphocytes and other cells . Transcripts for RGS1 were expressed at higher levels in β7- cells. RGS1 is a GTPase activating protein that regulates Gαi-stimulated pathways. Expression of RGS1 inhibits chemokine-induced cell migration and integrin-mediated adhesion in lymphocytes . Our data suggest that there may be less RGS1-mediated inhibition of chemokine signaling in β7+ cells. We speculate that the differential expression of KLRB1, NT5E, LGALS1, LGALS2, and RGS1 on β7+ and β7- T helper cell subsets may contribute to homing specificity by modulating the complex multistep process of cell adhesion and migration.
The primary activation of T cells leads to changes in the expression of integrin α4β7 and other molecules that control homing. It has recently been shown that upregulation of integrin α4β7 expression and increased responsiveness to the CCR9 ligand TECK occur within two days after activation of murine naïve CD4+ T cells in intestinal, but not cutaneous, lymph nodes  and that activation by dendritic cells from Peyer's patches but not peripheral lymph node or spleen promotes murine CD8+ T cell α4β7 expression and TECK responsiveness . We found that both KLRB1 and NT5E were virtually absent on CD45RA+ naïve CD4+ T cells and were expressed at low levels on CD45RA- CCR7+ central memory cells and on β7- CD45RA- non-gut homing memory effector cells but were expressed at higher levels in the β7high CCR7- CD45RA- memory effector subset. In contrast, LAIR1 was highly expressed on naïve T cells and on both CCR7- and CCR7+ β7+ CD45RA- cells but expression was lower on β7- CD45RA- cells. These results suggest that expression of α4β7 and expression of KLRB1, NT5E and LAIR1 may be coordinately regulated at the time of human T cell activation, as is apparently the case for α4β7 and CCR9 in mouse systems. Alternatively, it is possible that differences in expression arise from changes in gene expression that occur after the transition from naïve to memory effector cells or from the preferential retention of survival of particular memory effector cell subsets. Although we showed that expression of KLRB1, NT5E and LAIR1 was higher for the β7+ subset as a whole, many β7+ cells did not express these proteins and some β7- cells did. This suggests that the homing properties of individual T cells might be "fine tuned" by complex combinatorial regulation of molecules known to have major roles in determining organ-specific recruitment (e.g., integrin α4β7 and CCR9) and other molecules that can modulate adhesion and migration (e.g., KLRB1 and NT5E).
We used DNA microarrays to identify a set of gene transcripts that were differentially expressed on β7+ versus β7- blood memory CD4+ T cells. Some of these encode adhesion receptors (integrin α4 and L-selectin) and chemokine receptors (CCR9 and GPR2/CCR10) already known to be involved in organ-specific lymphocyte migration. Other differentially expressed transcripts encode additional molecules previously reported to affect cell adhesion and migration, including KLRB1, NT5E/CD73, LGALS1 and LGALS2 (galectin-1 and -2) and RGS1. As predicted from the transcript expression data, we found that KLRB1, NT5E and LAIR1 proteins were all preferentially expressed on the surface of β7+ versus β7- memory CD4+ T cells. Our results suggest that expression of several molecules that can modify T cell adhesion, endothelial transmigration and chemotaxis are also selectively regulated on CD4+ T cell subsets, perhaps during the "imprinting" process that takes place during initial T cell activation. These molecules are likely to contribute to the complex multistep process that regulates trafficking of CD4+ memory T cell subsets with different homing behaviors.
Isolation of β7+ and β7- lymphocytes from human blood
This protocol was approved by the Committee on Human Research at the University of California, San Francisco and informed consent was obtained from all subjects. Peripheral blood mononuclear cells (PBMC) were isolated from nine normal adult donors (six females and three males, ages 24–42 years) using sodium heparin coated Vacutainer Cell Preparation Tubes (Becton Dickinson) according to the manufacturer's instructions. PBMC were stained with CD4-FITC, CD45RA-Cy5 and anti-integrin β7-PE (all from BD Pharmingen). Anti-FITC microbeads and a MACS bead sorter (Miltenyi Biotec) were used to enrich for the CD4+ cells prior to flow cytometry. CD4+ memory (CD45RA- ) β7+ and β7- T cells were then purified using a FACS Vantage (Becton Dickinson).
Microarray analysis of transcript expression
Total RNA from β7+ and β7- CD4+ memory T cells was purified using the Mini RNA Isolation Kit (Zymo Research) and DNase treated using the DNA-free RNA Kit (Zymo Research) according to the manufacturer's instructions. RNA quality was evaluated using an Agilent Bioanalyzer. RNA amplification, labeling, and hybridization were performed as previously described with slight modifications . In brief, two rounds of amplification were performed using T7 RNA polymerase (Ambion MessageAmp aRNA Kit). Cy3 or Cy5 was incorporated into the amplified RNA products using amino allyl-modified nucleotides. Fluorescently-labeled amplified RNAs were fragmented using Ambion RNA Fragmentation Reagents and hybridized to DNA microarrays using Ambion SlideHyb Glass Array Hybridization Buffer #1. Each hybridization involved β7+ cell RNA from a single subject (labeled with one dye) and β7- cell RNA from the same subject (labeled with the other dye). A total of 27 arrays were used to analyze samples from the 9 subjects (at least 2 arrays per subject, including a dye swap).
Arrays were produced in our microarray facility using the Operon version 2 set of 70-mer oligonucleotide probes supplemented with some custom-designed 70-mers as described . Arrays included probes for 21357 genes plus control probes. After hybridization, arrays were scanned using an Axon GenePix 4000B scanner and images were processed using GenePix 5.0 software. The "print-tip loess" normalization was used to correct for within-array dye and spatial effects  and single channel quantile normalization was used to facilitate comparison between arrays . We used functions in the library marrayNorm  of the R / Bioconductor package  to perform these normalizations. After normalization we determined a log ratio, log2 (β7+ sample intensity/β7- sample intensity), for each probe on each array. No background subtraction was performed. Complete information about the array platform and data from each of the individual arrays is available from GEO  (GEO accession GSE1039). Appendix 1 [see additional file 1] is a MIAME-compliant description of the array experiments.
Identification of differentially expressed gene transcripts
A fixed effects linear model was used to estimate differences in transcript expression between β7+ and β7- CD4+ T cells. For each individual gene (probe) on the array, the model can be described as
Y ij = μ + A i + ε ij ,
where Y ij represents the normalized log ratio determined on a single array, i represents the subject number and j represents the array number. The parameter μ represents the actual log ratio of gene expression between β7+ and β7- cells, which we wished to estimate. A i represents the difference between the log ratio for subject i and the average log ratio for all subjects and ε denotes the experimental error. We fit the model using a zero sum constraint (ΣA i = 0). Fold difference was calculated from the estimated log ratio. We computed moderated t-statistics , log-odds ratios of differential expression (based on empirical Bayes shrinkage of the standard errors towards a common value ), and adjusted p-values (obtained using the Bonferroni correction) using functions in the limma library of the Bioconductor software package [41, 42]. Similar results were obtained under a random effects model (not shown).
Analysis of surface protein expression on blood CD4+ T cell subsets
Whole blood was collected from nine normal adult subjects (seven females and two males, ages 23–38 years, none of whom were included in the microarray experiments described above). Blood was stained with various antibody combinations and analyzed on a FACScalibur equipped for six color analysis. Antibodies recognizing CD4 (SK3), integrin β7 (FIB504), CD62L (DREG-56), CD73 (AD2), and CD161 (DX12) and isotype control antibodies were all from BD Biosciences. Other antibodies used were LAIR1 (DX26, generous gift of L. Lanier), KLRG1 (13A2, generous gift of D. Voehringer and H. Pircher), CD45RA (Immunotech), the anti-α4β7 mAb Act-1 , the anti-aEβ7 antibody HML-1 (Beckman Coulter), CCR7 (R&D Systems). Mean fluorescence intensity (MFI) was corrected by subtracting the MFI obtained with isotype control antibodies. The percentage of positive cells was determined by setting the threshold so that ≤1% of cells were considered positive after staining with control antibody.
Microarray studies were supported by Andrea Barczak, Michael Salazar, and the UCSF/San Francisco General Hospital General Clinical Research Center Core Genomics Laboratory (supported by grant M01-RR00083 from the National Center for Research Resources of the NIH). Flow cytometry was performed in the Flow Cytometry Core Laboratory of the J. David Gladstone Institutes. We thank Gordon Smyth and Mark Segal for helpful discussions regarding the microarray data analysis. The work was supported by NIH grant DK/AI54212.
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